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TestBoxMeshPartition.cpp
b5a1ba9bfadeefficient_neuronet

TestBoxMeshPartition.cpp
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			//@HEADER
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			// Kokkos v. 2.0
			// Copyright (2014) Sandia Corporation
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			// Under the terms of Contract DE-AC04-94AL85000 with Sandia Corporation,
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			#include <iostream>
			#include <stdexcept>
			#include <limits>
			#include <utility>
			#include <BoxMeshPartition.hpp>

			//----------------------------------------------------------------------------

			void test_box_partition( bool print )
			{
			const size_t np_max = 10000 ;

			const BoxBoundsLinear use_box ;

			BoxType root_box ;

			root_box[0][0] = 0 ; root_box[0][1] = 100 ;
			root_box[1][0] = 0 ; root_box[1][1] = 200 ;
			root_box[2][0] = 0 ; root_box[2][1] = 300 ;

			const size_t cell_total =
			( root_box[0][1] - root_box[0][0] ) *
			( root_box[1][1] - root_box[1][0] ) *
			( root_box[2][1] - root_box[2][0] );

			for ( size_t np = 2 ; np < np_max ; np = 2 * ( np + 1 ) ) {

			std::vector<BoxType> part_boxes( np );

			box_partition_rcb( root_box , part_boxes );

			size_t cell_goal = ( cell_total + np - 1 ) / np ;
			size_t cell_max = 0 ;

			for ( size_t i = 0 ; i < np ; ++i ) {
			cell_max = std::max( cell_max , count( part_boxes[i] ) );
			}

			if ( print ) {
			std::cout << std::endl
			<< "box_part( " << np
			<< " ) max( " << cell_max
			<< " ) goal( " << cell_goal
			<< " ) ratio( " << double(cell_max) / double(cell_goal)
			<< " )" << std::endl ;
			}

			const size_t nsample = std::min(np,(size_t)4);
			const size_t stride = ( np + nsample - 1 ) / nsample ;

			for ( size_t my_part = 0 ; my_part < np ; my_part += stride ) {
			BoxType my_use_box ;
			std::vector<size_t> my_use_id_map ;
			size_t my_count_interior ;
			size_t my_count_owned ;
			size_t my_count_uses ;
			std::vector<size_t> my_recv_counts ;
			std::vector<std::vector<size_t> > my_send_map ;

			size_t count_verify = 0 ;

			box_partition_maps( root_box , part_boxes ,
			use_box , my_part ,
			my_use_box , my_use_id_map ,
			my_count_interior ,
			my_count_owned ,
			my_count_uses ,
			my_recv_counts ,
			my_send_map );

			count_verify = my_count_owned ;

			if ( print ) {
			std::cout << " my_part(" << my_part << ") layout { "
			<< "P" << my_part
			<< "(" << my_count_interior
			<< "," << ( my_count_owned - my_count_interior )
			<< ")" ;
			}

			for ( size_t i = 1 ; i < np ; ++i ) {
			if ( my_recv_counts[i] ) {
			count_verify += my_recv_counts[i] ;
			const size_t ip = ( my_part + i ) % np ;

			if ( print ) {
			std::cout << " P" << ip << "(" << my_recv_counts[i] << ")" ;
			}

			// Compare recv & send lists

			BoxType ip_use_box ;
			std::vector<size_t> ip_use_id_map ;
			size_t ip_count_interior ;
			size_t ip_count_owned ;
			size_t ip_count_uses ;
			std::vector<size_t> ip_recv_counts ;
			std::vector<std::vector<size_t> > ip_send_map ;

			box_partition_maps( root_box , part_boxes ,
			use_box , ip ,
			ip_use_box , ip_use_id_map ,
			ip_count_interior ,
			ip_count_owned ,
			ip_count_uses ,
			ip_recv_counts ,
			ip_send_map );

			// Sent by ip, received by my_part:

			const BoxType recv_send = intersect( part_boxes[ip] , my_use_box );
			const size_t recv_send_count = count( recv_send );

			const size_t j = ( my_part + np - ip ) % np ;

			if ( recv_send_count != my_recv_counts[i] \|\|
			recv_send_count != ip_send_map[j].size() ) {
			throw std::runtime_error( std::string("bad recv/send map") );
			}
			}
			}
			if ( print ) { std::cout << " }" << std::endl ; }

			if ( count_verify != my_count_uses ) {
			throw std::runtime_error( std::string("bad partition map") );
			}
			}
			}
			}

lammps/lib/kokkos/example/multi_fem/TestBoxMeshPartition.cppb5a1ba9bfadeefficient_neuronet

TestBoxMeshPartition.cppView Options

lammps/lib/kokkos/example/multi_fem/TestBoxMeshPartition.cpp
b5a1ba9bfadeefficient_neuronet

TestBoxMeshPartition.cpp
View Options